Research on the Connectivity of Network

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Based on the characteristic of real network, this paper introduces traffic routing model, uses the capacity of network to measure the connectivity of network, establishes connectivity research model and finally we analyze the method for determining the capacity of network, and the relation between the connectivity of network with the capacity of each node (C) through simulation. Conclusions are shown as following: (1) It is feasible to use the capacity of network to measure the connectivity of network. (2) The capacity of network is measured by the critical generating rate Rc at which a continuous phase transition will occur from free state to congestion. (3) The connectivity of network is positively related with C, and the capacity of network shows a linear growth with the increasing of C. Results show that this evaluation of connectivity can better reflect the connectivity of real network, and well meets the research needs of real network.

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1412-1416

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June 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] WATTS D J, STROGATZ S H. Collective dynamics of small world networks[J]. Nature, 1998, 393: 440-442.

DOI: 10.1038/30918

Google Scholar

[2] Barabási A L, ALBERT R. Emergence of scaling in random networks[J]. Science, 1999, 286: 509-512.

Google Scholar

[3] ALBERT R, Barabási A L. Statistical mechanics of complex networks[J]. Rev of Modern Phys, 2002, 74: 47-97.

DOI: 10.1103/revmodphys.74.47

Google Scholar

[4] Liang Zhao, et al. Onset of traffic congestion in complex networks[J]. Physical Review E, 2005, 71(2): 026125.

Google Scholar

[5] Tadić B, Thurner S, Rodgers G J. Traffic on complex networks: Towards understanding global statistical properties from microscopic density fluctuations[J]. Physical Review E, 2004, 69(3): 036102.

DOI: 10.1103/physreve.69.036102

Google Scholar

[6] Yaozhong Shi, Xuewu Chen. Technical Evaluation Indicator and Standard In Highway Network Planning[J]. CHINA JOURNAL OF HIGHWAY AND TRANSPORT, 1995, 8(1): 120-124. (In Chinese).

Google Scholar

[7] Wuyang Yang, etc. Transportation Geography[M]. The commercial press, 1986(In Chinese).

Google Scholar

[8] Jun Xu, Songling Luo. A study of connectness for the highway network[J]. CHINA JOURNAL OF HIGHWAY AND TRANSPORT, 2000(01): 95-97. (In Chinese).

Google Scholar

[9] Wei Zhou, Shengrui Zhang, Hangshan Gao. A Study of the Comprehensive Evaluation for the Road Network Based on the Fuzzy Theory and Neural Network[J]. CHINA JOURNAL OF HIGHWAY AND TRANSPORT, 1997(04): 76-83. (In Chinese).

Google Scholar

[10] Jie Gao. Analysis of Transportation Network Connectivity Evaluation Index[J]. Journal of Transportation Systems Engineering and Information Technology, 2010(01): 35-38. (In Chinese).

Google Scholar

[11] Guimerà R, Diaz-Guilera A, Vega-Redondo F, et al. Optimal network topologies for local search with congestion[J]. Physical Review Letters, 2002, 89(24): 248701.

DOI: 10.1103/physrevlett.89.248701

Google Scholar

[12] Wenxu Wang, et al. Traffic dynamics based on local routing protocol on a scale-free network[J]. Physical Review E, 2006, 73(2): 026111.

Google Scholar

[13] Wenxu Wang, et al. Integrating local static and dynamic information for routing traffic[J]. Physical Review E, 2006, 74(1): 016101.

Google Scholar

[14] Gang Yan, et al. Efficient routing on complex networks[J]. Physical Review E, 2006, 73(4): 046108.

Google Scholar

[15] Arenas A, Díaz-Guilera A, Guimera R. Communication in networks with hierarchical branching[J]. Physical Review Letters, 2001, 86(14): 3196.

DOI: 10.1103/physrevlett.86.3196

Google Scholar